The term expert system is rapidly
becoming a new catch-phrase, like user-friendly. Some people point to
"smart" computers now being used for diagnosis and trouble-shooting in
medicine and industry as proof that expert systems are possible and
practical. Even some personal computer software publishers claim that
their products possess artificial intelligence or expert system
capabilities. But others maintain that few, if any, true expert systems
really exist. Here's a look at what's happening.If an
"expert" is defined as someone who knows more than most people about a
given subject, then you probably seek advice from several experts every
week. If you or someone in your family is ill, you probably go to a
physician. After asking several questions and running some tests, the
doctor arrives at a diagnosis and recommends treatment. If your car
keeps stalling at intersections, you probably take it to a mechanic,
who checks the car and recommends a repair. If you find yourself owing
too much federal income tax on April 15, a tax consultant can offer
ways to help. And if you think you've been wronged by someone, a lawyer
can usually decide if it's worthwhile to bring a lawsuit.
All of these people you consult-these experts-are
trusted to have a sufficient database
of knowledge in certain areas so that their advice is worth
following (and worth paying for).
You can also buy programs for your personal computer
that have been designed to act as consultants in such areas as personal
finance and health care. Are they replacements for real experts? Not
according to their publishers, who stress that the programs are
consultants only, and that you should almost always seek additional
help from professionals.
But the day may not be too distant when a new type
of computer program will replace
experts-or at least, take over part of what experts do. These
sophisticated programs, called expert
systems, contain a database of knowledge that human experts can
spend years acquiring. More significantly, the most advanced expert
systems now under development also incorporate some of the rules of
logic and analysis that experts combine with their storehouse of facts
to solve real-life problems. Already, there are programs in everyday
use that analyze geological data to find likely spots for new
reservoirs of oil-a job which was formerly the exclusive domain of
geologists and engineers.
Some people even believe that expert systems will
become commonplace on the next generation of home computers, bringing
the advice of family doctors and other professionals into the home at
the touch of a key. But others warn that the premature application of
expert systems could result in serious trouble, especially if they're
based on an incomplete understanding of the decision-making process.
Though still in their infancy, expert systems are
opening another chapter in the debate over artificial intelligence.

Several
years ago, Joseph Weizenbaum, professor of computer science at the
Massachusetts Institute of Technology (MIT), wrote a computer program
called Eliza. His intention
was to show how a computer could act like a psychologist. Eliza would ask the user questions
about how he or she was feeling, then pick up on key words or phrases
in the answer to guide its "therapy."
Some people are now calling Eliza an early expert system.
"I hadn't even heard that phrase used when I wrote
it," says Weizenbaum today.
Part of the challenge of designing an expert system
is deciding on the definition of what it's supposed to be and how it's
supposed to work: Even the experts can't agree. For example, Weizenbaum
thinks Eliza is being
characterized as an early expert system because he consulted experts
before writing it. Although Eliza may
seem like it's really listening to you and responding, the program just
follows a set of rules given it by Weizenbaum. If you say you're having
a bad day, the program may ask you to talk about it. Then it may ask
how certain events made you feel, or what you think you should do about
it. Eliza is really more of an interactive diary than an expert.
Now the term expert system appears to be changing to
apply to systems that perform expertly.
That's still too vague, says Weizenbaum. "If one
were to characterize systems that perform expertly as expert systems,
then huge libraries of scientific and business programs that have
accumulated over the years-many of which are doing a perfectly expert
job at whatever they do-would all be expert systems. So it's not a very
precise term.
"Here is an example of something that nobody
considers to be an expert system: Today, almost all landings of
wide-bodied airplanes are done automatically by onboard computers. I
often wonder what the world would be like if that particular work had
been done at the AI (artificial intelligence) lab at MIT or Stanford. I
don't think we'd ever hear the end of it. But as a matter of fact, it
was done, one might say, anonymously. I have no idea who did it, and
certainly it does a job that it takes a lot of years to train a human
being to do, but it's not considered an expert system. That's odd."

Yet,
defining an expert system isn't as simple as pointing to a computer
which replaces the performance of a human. Computers have been doing
that for years. For instance, though they may not be labeled by some
academics as expert systems, process
control computers perform functions previously carried out by
people with extensive training. "Today, for example, one can see a very
large-I mean acres and acres-petroleum processing factory, and if you
look very, very hard, you might find two people in these hundreds of
acres," says Weizenbaum. "The whole thing is done under computer
control.
"So there's this whole world of computerized process
control which has been doing this for a long, long time, and it doesn't
think of itself, or hasn't, as expert control."
Instead, true expert systems seem to be defined
according to their evolution and architecture - such as a database of
rules and inference mechanisms. Process control computers were
developed by other means. "There are lots of process control
applications that have been done very well that today might have been
tackled differently in the light of expert systems," says Weizenbaum.
The point at which expert systems cross the border
of artificial intelligence is hazier still. To some, there is a
definite difference; to others, a perfectly functioning expert
system implies artificial
intelligence.
Part of the problem is that AI researchers diverge
over how to approach the development of expert systems and artificial
intelligence. A long time ago, says Weizenbaum, those in the field
recognized two fundamentally different ways of doing business.
The first is to look at AI basically as a branch of
psychology; that is, to use a computer to understand the operations of
the human mind by programming it do high-level tasks as we think a
human mind might do them. The other approach is to program a computer
to do very clever things that ordinarily would require human
intelligence, but to perform the tasks in ways that might not be
considered by (or even possible for) a human being.

These
two schools of thought are referred to as theory mode and performance mode. Weizenbaum gives
an example of theory mode:
"Very early on, people got interested in the idea of
computers playing chess. It was thought that if we could find out
somehow what goes on in a chess player's mind and somehow program that
into the computer, not only would we have a good chess-playing machine,
but we'd also learn a lot about psychology, about human thought
processes. People started trying to do that, but if nothing else,
people got tempted to take shortcuts, to take advantage of some
features that were built into the computer that no one thought were
built into the human mind.
"So from the very beginning, the temptation couldn't
be resisted, and people started designing chess playing programs which
took enormous advantage of all the peculiarities of computers but left
behind any consideration of how the mind does it. And today we have
powerful chess-playing computers, without the slightest claim that they
teach us anything at all about human thinking.
"We've sort of drifted from theory into performance
mode."
And due to a number of circumstances, including the
military's interest in and funding of performance mode AI research,
says Weizenbaum, there's very little theory work going on today.
One place where theory work is being pursued is at
the University of California at San Diego, in a research center called
the Institute for Cognitive Science. Paul Smolensky, one of the
researchers there, has been primarily involved in research on neurally
inspired mathematical models of learning, memory processes, and problem
solving. Using what are currently believed to be some very general
characterizations of the brain, Smolensky's work is focused on one
primary area: to understand people, and how to educate them and advance
knowledge in scientific fields.
An outgrowth of this research is that it suggests
various kinds of novel computers that could be built-such as connecting
lots of processors together and letting them work in parallel the same
way neurons work in the brain. Only a few prototypes of such machines
exist today.
"There's the platonic idea of what an expert system
is, and then there's a whole bunch of actual systems that people have
developed that they use the label for," says Smolensky. "I'm not aware
of any that are actually in practice except the one that everyone in
computer science is aware of, and that's the DEC [Digital Equipment
Corporation] expert system for designing installations of their VAX
computer systems."
This expert system, called R1/XCON, was developed by
Dr. John McDermott, principal scientist and associate head of the
computer science department at CarnegieMellon University. It configures
a VAX minicomputer system to the customer's specifications, saving DEC
more than $2.5 million annually in field costs. R1/XCON takes roughly a
minute to execute the work it took its human predecessors an hour to
complete.
McDermott and a number of other scientists,
engineers, and programmers at Carnegie-Mellon have formed a corporation
called the Carnegie Group to design and market AI-based systems for
commercial applications. The Carnegie Group is looking into many areas
that could benefit from expert systems, including engineering design,
project management, production management, and sensor-based machine
diagnosis and control.

One of the first
steps in creating an expert system is to interview the experts the
program is supposed to emulate. By asking a series of highly detailed
questions, the designers try to figure out the decision-making process
they'll attempt to reconstruct in the program. When this thinking
process is coupled with a database of facts, the ideal expert system
should have a similar capacity for analyzing information and arriving
at the right decision.
A potential flaw has been cited in this approach,
however: the difficulty of taking into account the role of human
intuition, and even emotion, in decision-making.
This is a vital point for some critics of expert
systems and artificial intelligence. For instance, if you ask someone
what the movie War Games was about, they'll probably say something
like, "Oh, this kid broke into the national defense system with his
home computer and almost started a nuclear war." But the defense system
wasn't exposed to this vulnerability until after the government decided
that human beings could not be trusted to enter the codes and push the
buttons that would launch our nuclear weapons. So the weapons were
placed under computer control, because computers would not falter for
emotional reasons at the crucial moment.
"There's a tremendous amount of human judgment that
has to go into a decision about whether to give a computer a certain
role in a decision-making system," says Smolensky.
Computers may be able to take over jobs previously
done by human beings, but that does not make them intelligent, let
alone experts, he says. "Expertise derives in a very significant way
from intuition and intuitive processes. Experts do not have any access
to that when they introspect about how they do what they do, and no
amount of asking an expert questions is going to get at the information
and the knowledge that allows the expert to do what he or she does. And
if we're going to understand expertise, we have to understand
intuition."
Smolensky warns of the dangers of employing too
much technology too fast, especially in areas that have a direct effect
on human life. He points out that even when a relatively simple
computer system is first installed in a business, there are inevitable
last-minute bugs and problems that must be solved before it functions
smoothly. "Am it's only because these systems car make a lot of bad
mistakes and people can go in and fix them afterward-basically putting
Band-Aids on top of Band-Aids on top of Band-Aids-that we don't have a
lot of permanent disaster stories.
"If you look at the problem of making decisions
intelligently as something that we can only under stand when we
understand intuition, and if you realize that intuition is something
that we're not going to understand for a long time, then you realize
that we shouldn't be giving computers the power to make decisions that
are important."